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Config

pycodeloop.core.config.Config

Import

You can import the Config class with:

from pycodeloop import Config
from pycodeloop.providers import GenericProvider
Example

class pycodeloop.core.config.Config

config = Config(
    provider=GenericProvider.from_json("path/to/config.json"),
)

Parameters:

Name Type Description Default
provider Optional[Provider]

LLM backend driving the agent — always a GenericProvider under the hood. Defaults to the provider named by the PYCODELOOP_PROVIDER env var (a path to a JSON config file, a bare "generic" name, or a 'module.path:ClassName'; a bundled Anthropic config when unset).

 None
tools Optional[List[Tool]]

Tools exposed to the agent. Defaults to the built-in read/write/edit/grep/bash set.

 None
system_prompt Optional[str]

Overrides the default system prompt.

 None
max_turns int

Hard cap on tool-use loop iterations.

 MAX_TURNS
max_history_turns Optional[int]

Cap the session on the number of most recent user-initiated turns kept — older turns are dropped as a whole unit (never mid tool_calls/ tool_result) before each provider call. Defaults to 20; pass None to let the session grow without bound instead.

 20
skills bool

Discover Claude Code skills/memory, Cursor rules, and AGENTS.md files on this machine and this project, expose them as a read_skill tool, and list them in the system prompt so the agent knows what's available.

 False
skill_sources Optional[Set[str]]

Limit discovery to these sources ("claude-skill", "claude-memory", "cursor-rule", "agents-md"). Defaults to all of them.

 None
skills_refresh bool

Skip the ~/.pycodeloop/config.json skills cache and force a full rescan.

 False
storage Optional[Sessions]

Persists the session so CodeLoop.run(prompt, session_key=...) can resume a conversation across process restarts. Defaults to SqliteSessions() (~/.pycodeloop/pycodeloop.db). Pass False to keep sessions in memory only, for the life of the CodeLoop instance.

 None

Attributes:

Name Type Description
provider Provider
tools List[Tool]
system_prompt Optional[str]
max_turns int
skills List[Skill]
storage Optional[Sessions]
Source code in pycodeloop/core/config.py 
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class Config:
    """
    Import:
        You can import the **Config** class with:

            from pycodeloop import Config
            from pycodeloop.providers import GenericProvider

    Example:
        `class` pycodeloop.core.config.Config

            config = Config(
                provider=GenericProvider.from_json("path/to/config.json"),
            )

    Args:
        provider (Optional[Provider]): LLM backend driving the agent —
            always a `GenericProvider` under the hood. Defaults to the
            provider named by the `PYCODELOOP_PROVIDER` env var (a
            path to a JSON config file, a bare `"generic"` name, or a
            `'module.path:ClassName'`; a bundled Anthropic config when
            unset).

        tools (Optional[List[Tool]]): Tools exposed to the agent.
            Defaults to the built-in read/write/edit/grep/bash set.

        system_prompt (Optional[str]): Overrides the default system
            prompt.

        max_turns (int): Hard cap on tool-use loop iterations.

        max_history_turns (Optional[int]): Cap the session on the
            number of most recent user-initiated turns kept — older
            turns are dropped as a whole unit (never mid tool_calls/
            tool_result) before each provider call. Defaults to `20`;
            pass `None` to let the session grow without bound instead.

        skills (bool): Discover Claude Code skills/memory, Cursor rules,
            and AGENTS.md files on this machine and this project, expose
            them as a `read_skill` tool, and list them in the system
            prompt so the agent knows what's available.

        skill_sources (Optional[Set[str]]): Limit discovery to these
            sources ("claude-skill", "claude-memory", "cursor-rule",
            "agents-md"). Defaults to all of them.

        skills_refresh (bool): Skip the `~/.pycodeloop/config.json` skills
            cache and force a full rescan.

        storage (Optional[Sessions]): Persists the session so
            `CodeLoop.run(prompt, session_key=...)` can resume a
            conversation across process restarts. Defaults to
            `SqliteSessions()` (`~/.pycodeloop/pycodeloop.db`). Pass `False`
            to keep sessions in memory only, for the life of the
            `CodeLoop` instance.

    Attributes:
        provider (Provider):
        tools (List[Tool]):
        system_prompt (Optional[str]):
        max_turns (int):
        skills (List[Skill]):
        storage (Optional[Sessions]):
    """

    _PROVIDERS = {"provider": Provider, "storage": Sessions}

    def __init__(
        self,
        provider: Provider | None = None,
        tools: list[Tool] | None = None,
        system_prompt: str | None = None,
        max_turns: int = Settings.MAX_TURNS,
        max_history_turns: int | None = 20,
        skills: bool = False,
        skill_sources: set[str] | None = None,
        skills_refresh: bool = False,
        storage: Sessions | bool | None = None,
    ) -> None:
        self.provider = provider if provider is not None else _default_provider()
        self.tools = list(tools) if tools is not None else list(DEFAULT_TOOLS)
        self.system_prompt = system_prompt
        self.max_turns = max_turns
        self.max_history_turns = max_history_turns
        self.skills = self._discover_skills(skills, skill_sources, skills_refresh)
        self.storage = None if storage is False else storage or _default_storage()

        self._validate()

    def _discover_skills(
        self, enabled: bool, sources: set[str] | None, refresh: bool
    ) -> list:
        if not enabled:
            return []

        found = discover_skills(sources=sources, use_cache=not refresh)

        if not found:
            return found

        self.tools = [*self.tools, ReadSkillTool(found)]
        base_prompt = (
            self.system_prompt
            if self.system_prompt is not None
            else DEFAULT_SYSTEM_PROMPT
        )
        self.system_prompt = f"{base_prompt}\n\n{render_skills_index(found)}"
        return found

    def _validate(self) -> None:
        for name, abc in self._PROVIDERS.items():
            value = getattr(self, name)

            if value is not None and not isinstance(value, abc):
                raise NotProviderInstance(name=name)

max_history_turns = max_history_turns instance-attribute

max_turns = max_turns instance-attribute

provider = provider if provider is not None else _default_provider() instance-attribute

skills = self._discover_skills(skills, skill_sources, skills_refresh) instance-attribute

storage = None if storage is False else storage or _default_storage() instance-attribute

system_prompt = system_prompt instance-attribute

tools = list(tools) if tools is not None else list(DEFAULT_TOOLS) instance-attribute

__init__(provider=None, tools=None, system_prompt=None, max_turns=Settings.MAX_TURNS, max_history_turns=20, skills=False, skill_sources=None, skills_refresh=False, storage=None)

Source code in pycodeloop/core/config.py 
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def __init__(
    self,
    provider: Provider | None = None,
    tools: list[Tool] | None = None,
    system_prompt: str | None = None,
    max_turns: int = Settings.MAX_TURNS,
    max_history_turns: int | None = 20,
    skills: bool = False,
    skill_sources: set[str] | None = None,
    skills_refresh: bool = False,
    storage: Sessions | bool | None = None,
) -> None:
    self.provider = provider if provider is not None else _default_provider()
    self.tools = list(tools) if tools is not None else list(DEFAULT_TOOLS)
    self.system_prompt = system_prompt
    self.max_turns = max_turns
    self.max_history_turns = max_history_turns
    self.skills = self._discover_skills(skills, skill_sources, skills_refresh)
    self.storage = None if storage is False else storage or _default_storage()

    self._validate()